Inhibition of pyrite oxidation by a phospholipid in the presence of silicate

The influence of sodium silicate on the ability of a diacetylene-containing phospholipid (23:2 diyne PC) to inhibit the oxidation of pyrite at pH 2 and pH 6 was investigated. The phospholipid used has previously been reported to show up to 80% suppression of pyrite oxidation and to show excellent stability down to at least pH 2. Pyrite was leached with a solution containing Fe3+ but no coating agent and three different solutions or treatments: a lipid treatment, a silicate treatment, and a lipid + silicate treatment. Pyrite oxidation was based on iron (Fe3+, Fe2+) leached out of a continuous-flow porous-bed reactor system. The results show that at pH 6 the silicate and lipid both bind strongly to the pyrite surfaces, providing a barrier that inhibits the production and subsequent release of oxidation products. The lipid is superior to the silicate in suppressing pyrite oxidation at both pH 2 and pH 6. Also, the presence of silicates decreased the ability for the lipid to suppress pyrite oxidation, both at pH 2 and pH 6. The reaction mechanism for pyrite oxidation at pH 2 is first order for pyrite leached by solutions containing only ferric, ferric together with silicate, and ferric combined with silicate and lipid. The only treatment that effectively prevented pyrite oxidation at pH 2 was the lipid treatment. The Fe speciation results are supported by both SEM images and EDS calculations.     

Flow of materials in rotary kilns used for sponge iron manufacture: Part II. Effect of kiln geometry

The present work identifies the basic features of burden movement in a rotary kiln. The cold model study was conducted with iron ore as the feed material to determine the influence of length to diameter ratio (L/D) of a rotary kiln on the filling degree, hold-up, and residence time of the charge. An empirical equation correlating different operating variables has been derived on the basis of the experimental results. The influence of individual parameters under different conditions on the residence time and back spillage has also been evaluated. Formerly Joint Director, Research and Development, TISCO     

Structure and properties of diffusion bonded transition joints between commercially pure titanium and type 304 stainless steel using a nickel interlayer

The solid-state diffusion bonding was carried out between commercially pure titanium and Type 304 stainless steel using nickel as an interlayer in the temperature range of 800–900 °C for 9 ks under 3 MPa load in vacuum. The transition joints thus formed were characterized in the optical and scanning electron microscopes. The inter-diffusion of the chemical species across the diffusion interfaces were evaluated by electron probe microanalysis. TiNi₃, TiNi and Ti₂Ni are formed at the nickel–titanium (Ni–Ti) interface; however, the stainless steel–nickel (SS–Ni) diffusion interface is free from intermetallic compounds up to 850 °C temperature. At 900 °C, the Ni–Ti interface exhibits the presence of α-β Ti discrete islands in the matrix of Ti₂Ni and λ + χ + α-Fe, λ + FeTi and λ + FeTi + β-Ti phase mixtures occur at the SS–Ni interface. The occurrence of different intermetallics are confirmed by the x-ray diffraction technique. The maximum tensile strength of ∼276 MPa and shear strength of ∼209 MPa along with 7.3% elongation were obtained for the diffusion couple processed at 850 °C. At the 900 °C joining temperature, the formation of Fe–Ti base intermetallics reduces the bond strength. Evaluation of the fracture surfaces using scanning electron microscopy and energy dispersive spectroscopy demonstrates that failure takes place through Ni–Ti interface up to 850 °C and through the SS–Ni interface of the joint when processed at 900 °C.     

Wavelet Bootstrap Multiple Linear Regression Based Hybrid Modeling for Daily River Discharge Forecasting

A new hybrid model, the wavelet–bootstrap–multiple linear regression (WBMLR) is proposed to explore the potential of wavelet analysis and bootstrap resampling techniques for daily discharge forecasting. The performance of the developed WBMLR model is also compared with five more models: multiple linear regression (MLR), artificial neural network (ANN), wavelet-based MLR (WMLR), wavelet-based ANN (WANN) and wavelet–bootstrap–ANN (WBANN) models. Seven years of discharge data from seven gauging stations in the middle reaches of Mahanadi river basin in India are applied in this study. Significant input vectors are decomposed into discrete wavelet components (DWCs) using discrete wavelet transformation (DWT) to generate wavelet sub time series that are used as inputs to the MLR and ANN models to develop the WMLR and WANN models, respectively. Effective wavelets are selected by considering several types of wavelets with different vanishing moments. WBMLR and WBANN models are developed as ensemble of different WMLR and WANN models, respectively, developed using different realizations of the training dataset generated using bootstrap resampling technique. The results show that the wavelet bootstrap hybrid models (i.e. WBMLR and WBANN) produce significantly better results than the traditional MLR and ANN models. Hybrid models based on MLR (WMLR, WBMLR) perform better than the ANN based hybrid models (WBANN, WANN). The WBMLR and WMLR models simulate the peak discharges better than the WBANN, WANN, MLR and ANN models, whereas the overall performance of WBMLR model is found to be more accurate and reliable than the remaining five models.     

Pattern synthesis of centre fed linear array using Taylor one parameter distribution and restricted search Particle Swarm Optimization

In this article, a new method of pattern synthesis of centre fed, equal distance linear array having single and multiple synthesis objectives has been proposed and statistically investigated. Single objective of reduced side lobe level (SLL) and first null beamwidth (FNBW) has been considered separately. Consequently, multiple objectives of beamwidth and side lobe level have been investigated. Synthesis of linear array for suitable objectives has been investigated on Taylor one parameter distribution with equal progressive phase. Excitation amplitude of each array element is taken as optimization parameter where distribution has been optimized using Particle Swarm Optimization (PSO) for achieving low SLL. Later the same has been incorporated for obtaining suitable FNBW. In our optimization algorithm conventional PSO has been modified with a restricted search PSO (RSPSO) where search space has been predefined within excitation amplitude range. PSO within the defined range searches for optimum excitation amplitude to achieve the desired objectives. In order to illustrate the effectiveness of the proposed RSPSO, simulation results of three significant instances of linear array have been presented for both even and odd number of element. The design results obtained using RSPSO have improved result than those obtained using other state of the art evolutionary algorithms like differential evolution (DE), invasive weeds optimization (IWO) and Conventional particle Swarm optimization (CPSO) in a statistically significant way.     

A copper–cyclen coordination complex associated with a polyoxometalate anion: Synthesis,crystal structure and electrochemistry of [Cu(cyclen)(MeCN)][W6O19]

The reaction between Cu(NO₃)₂·3H₂O and a tetra-aza macrocycle, more specifically, cyclen in 1:1 MeCN–MeOH solvent mixture forms a Cu²⁺–cyclen coordination complex in situ, that has been reacted with an isopolyanion [W₆O₁₉]^2? in a slow diffusion technique, resulting in the isolation of an ion-pair solid [Cu(cyclen)(MeCN)][W₆O₁₉] (1). Single crystal structural investigation on 1 shows a square pyramidal geometry around the metal centre (copper ion) with an axially bound MeCN solvent molecule. The title compound 1 is the first crystallographically characterized ion-pair compound, in which a transition metal coordination complex of a tetra-aza-crown ether (cyclen) has been associated with a polyoxometalate cluster anion. This communication deals with synthesis, spectroscopic, structural and electrochemical analyses of compound 1.     

Conventional and Unconventional Mechanisms by which Exocytosis Proteins Oversee β-cell Function and Protection

Type 2 diabetes (T2D) is one of the prominent causes of morbidity and mortality in the United States and beyond, reaching global pandemic proportions. One hallmark of T2D is dysfunctional glucose-stimulated insulin secretion from the pancreatic β-cell. Insulin is secreted via the recruitment of insulin secretory granules to the plasma membrane, where the soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) and SNARE regulators work together to dock the secretory granules and release insulin into the circulation. SNARE proteins and their regulators include the Syntaxins, SNAPs, Sec1/Munc18, VAMPs, and double C2-domain proteins. Recent studies using genomics, proteomics, and biochemical approaches have linked deficiencies of exocytosis proteins with the onset and progression of T2D. Promising results are also emerging wherein restoration or enhancement of certain exocytosis proteins to β-cells improves whole-body glucose homeostasis, enhances β-cell function, and surprisingly, protection of β-cell mass. Intriguingly, overexpression and knockout studies have revealed novel functions of certain exocytosis proteins, like Syntaxin 4, suggesting that exocytosis proteins can impact a variety of pathways, including inflammatory signaling and aging. In this review, we present the conventional and unconventional functions of β-cell exocytosis proteins in normal physiology and T2D and describe how these insights might improve clinical care for T2D.     

Junction Temperature Measurements and Thermal Modeling of GaInN/GaN Quantum Well Light-Emitting Diodes

We present a junction temperature analysis of GaInN/GaN quantum well (QW) light-emitting diodes (LEDs) grown on sapphire and bulk GaN substrate by micro-Raman spectroscopy. The temperature was measured up to a drive current of 250 mA (357 A/cm²). We find better cooling efficiency in dies grown on GaN substrates with a thermal resistance of 75 K/W. For dies on sapphire substrates we find values as high as 425 K/W. Poor thermal performance in the latter is attributed to the low thermal conductivity of the sapphire. Three-dimensional finite-element simulations show good agreement with the experimental results, validating our thermal model for the design of better cooled structures.